Autonomous, randomly coupled, neural networks display a transition to chaos at a critical
coupling strength. Here, we investigate the effect of a time-varying input on the onset of chaos …

Correlated neuronal activity is a natural consequence of network connectivity and shared
inputs to pairs of neurons, but the task-dependent modulation of correlations in relation to …

Mathematical and statistical models have played important roles in neuroscience, especially
by describing the electrical activity of neurons recorded individually, or collectively across …

The diversity of neuron models used in contemporary theoretical neuroscience to investigate
specific properties of covariances in the spiking activity raises the question how these …

The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous
networks of point neurons or neurons with a small number of compartments. It aims at …

Correlations in spike-train ensembles can seriously impair the encoding of information by
their spatio-temporal structure. An inevitable source of correlation in finite neural networks is …

Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and
parameters of their constituents. At cellular resolution, the entities of theory are neurons and …

State-of-the-art software tools for neuronal network simulations scale to the largest computing
systems available today and enable investigations of large-scale networks of up to 10% of …

MUSIC is a standard API allowing large scale neuron simulators to exchange data within a
parallel computer during runtime. A pilot implementation of this API has been released as …

Many qualitative features of the emerging collective dynamics in neuronal networks, such
as correlated activity, stability, response to inputs, and chaotic and regular behavior, can be …